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- Tasks: Refine and optimise models predicting marketing image conversion rates using cutting-edge tech.
- Company: Join a dynamic team supporting major clients in innovative data science projects.
- Benefits: Competitive day rate, remote work flexibility, and potential for contract extension.
- Why this job: Make a real impact on marketing analytics with your data science skills.
- Qualifications: Experience in data science, ML, and strong Python coding skills required.
- Other info: Fast-paced environment with opportunities for growth in data and AI projects.
The predicted salary is between 48000 - 72000 £ per year.
Freelance Lead Data Scientist Start: Within 1–2 weeks) Contract: 1 month (strong potential to extend – Inside preferred for extensions) Day Rate: £600/day (Inside or Outside IR35 considered) Location: Remote (UK-based preferred; preferred onsite for initial few days We’re supporting a major client on a short, high-impact project that blends computer vision , NLP , and marketing analytics . The goal is to refine and optimise an existing model that predicts the conversion rate of marketing images based on their visual and contextual attributes. The work: Enhance or rebuild an existing multimodal image-to-text model built using CLIP and Phi (OpenAI). Apply SHAP (or similar explainability methods) to attribute what’s driving conversion — e.g., the presence of people, objects, or scene context. Extend an interactive Python Dash web app that visualises image predictions and their drivers. Work closely with the analytics and marketing teams to make the tool usable, explainable, and business-ready. Handle both model optimisation and dash app refinement , focusing on interpretability and usability. Tech environment: Python | CLIP | Phi | SHAP | Computer Vision | NLP | Dash | Pandas | NumPy Ideal profile: Proven experience in data science / ML , with practical exposure to computer vision and explainable AI . Strong coding in Python , with experience building models end-to-end and deploying lightweight web apps (Dash/Streamlit). Understanding of model explainability (SHAP, LIME, feature attribution) . Hands-on with multimodal data (images + text) preferred. Comfortable in a fast-moving, creative environment; self-starter with a growth mindset. Contract length: 4–5 weeks initially, strong chance of extension into wider data/AI projects
Data Scientist - Image Conversion Probability employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Image Conversion Probability
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who have experience with computer vision and NLP. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving image conversion and explainability methods like SHAP. This will give potential clients a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Be proactive! Don’t just wait for job postings; reach out directly to companies you admire. Let them know you’re interested in freelance opportunities and how your skills can help them refine their models.
✨Tip Number 4
Apply through our website! We’ve got a streamlined process that makes it easy for you to showcase your expertise in Python, CLIP, and Dash. Plus, we love seeing candidates who are eager to jump into exciting projects!
We think you need these skills to ace Data Scientist - Image Conversion Probability
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with computer vision, NLP, and model optimisation. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about this project and how your background makes you the perfect fit. Keep it engaging and relevant to the job description.
Showcase Your Technical Skills: Since we’re looking for someone with strong Python skills and experience with tools like CLIP and SHAP, make sure to mention specific projects where you’ve used these technologies. We love seeing practical examples!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Don’t miss out!
How to prepare for a job interview at Xcede
✨Know Your Tech Inside Out
Make sure you’re well-versed in the tech stack mentioned in the job description, especially Python, CLIP, and SHAP. Brush up on your knowledge of computer vision and explainable AI, as these will likely be hot topics during your interview.
✨Showcase Your Projects
Prepare to discuss specific projects where you've applied your skills in data science and machine learning. Highlight any experience with multimodal data and how you’ve optimised models or built web apps using Dash or Streamlit.
✨Understand the Business Context
Familiarise yourself with marketing analytics and how image conversion rates impact business outcomes. Being able to connect your technical skills to real-world applications will impress the interviewers and show that you’re not just a techie but also a strategic thinker.
✨Ask Insightful Questions
Prepare thoughtful questions about the project and the team dynamics. Inquire about the challenges they face with the current model and how they envision the role contributing to their goals. This shows your genuine interest and helps you assess if it’s the right fit for you.
